The continued expansion of the Internet mandates an equal expansion of systems for searching for desired content on the Internet. Search engine sites have become portals through which most users find the content they seek; however, the technology behind search engines remains ineffective in presenting relevant results and connecting users from one relevant result to other relevant results.
The predominant method by which the Internet is searched is keyword-based. In the context of Internet searching, and as used in this application, a “keyword” comprises one or more words that are used as a search term. In the simplest model, a user provides a keyword or multiple keywords, and sites are ranked according to the number of uses of keywords, and results are delivered based on this ranking. Keywords in metatags may be treated as more important than keywords in other locations, and the rate at which pages are clicked by searchers using a keyword, may be a further basis for ranking pages.
Search engines have long sought a ‘natural language’ method for accepting queries from users, but this is fraught with difficulties, and most sophisticated searchers forego the use of natural language interfaces in favor of so-called ‘advanced’ search methods. For example, on Google, the advanced search options permit a user to identify required keywords, keywords that identify results to be excluded, groups of keywords, one of which must appear in a result, numbers in particular ranges, languages, regions, update dates, specific domains, locations of keywords, reading level of the page, file types, and usage rights. This ‘advanced’ method, however, can be difficult to understand and use effectively, and perhaps because of this the advanced search method is not readily and conspicuously offered to a searcher on Google.
It has been proposed to search for documents by identifying word clusters in a source document, and using these to search for similar occurrences in other documents, such as in U.S. Pat. No. 7,844,566, the entirety of which is incorporated by reference herein. This method, however, requires the searching computer to evidence a great deal of understanding of linguistic meaning and context, in order to properly identify the words from a source document to include in the searched word clusters and, in addition, evaluate whether the found results are or are not similar in subject to the source document. U.S. Pat. No. 7,769,771, the entirety of which is incorporated by reference herein, describes a method that uses a visual depiction of the relevance of documents and uses seed documents to create a search for additional documents.
Other keyword based search methods and computer systems for performing such methods are disclosed in U.S. Pat. Nos. 6,775,677, 5,926,812 and 5,857,179, each of which is incorporated by reference herein in its entirety.
U.S. patent application Ser. No. 13/608,715, filed Sep. 10, 2012 by the inventors of this application, and incorporated herein in its entirety, discloses a keyword based search methodology in which the user defines relative importance settings for each keyword, so that the user can change the relative importance of one keyword relative to at least one other keyword when the two keywords are used in conjunction as part of a query. The relative importance setting may be a numeric value such as an integer between 1 and 10 or 1 and 100, a fractional or floating or fixed precision decimal value, or may be a discrete variable having values selected from a set such as (low, medium, high). This method advantageously provides more discrete control over the way a search is performed than even the “advanced” search methods on Google and other search engines. However, even this method has the drawback that the user must define the keywords to be used, and may miss search results if concepts may be expressed in linguistic forms that do not use the chosen keywords.
Thus, despite the extensive development referenced above, there is a need for a searching method that permits intuitive management and targeting of specific keywords, in a way that can take advantage of human knowledge and understanding of words and context, yet remains intuitive to searchers.